P A Lipton1, H Eichenbaum. 1. Center for Memory and Brain, Department of Psychology, Boston University, 2 Cummington street, Boston, MA 02215, USA.
Abstract
Spatial mapping and navigation are figured prominently in the extant literature that describes hippocampal function. The medial entorhinal cortex is likewise attracting increasing interest, insofar as evidence accumulates that this area also contributes to spatial information processing. Here, we discuss recent electrophysiological findings that offer an alternate view of hippocampal and medial entorhinal function. These findings suggest complementary contributions of the hippocampus and medial entorhinal cortex in support of episodic memory, wherein hippocampal networks encode sequences of events that compose temporally and spatially extended episodes, whereas medial entorhinal networks disambiguate overlapping episodes by binding sequential events into distinct memories.
Spatial mapping and navigation are figured prominently in the extant literature that describes hippocampal function. The medial entorhinal cortex is likewise attracting increasing interest, insofar as evidence accumulates that this area also contributes to spatial information processing. Here, we discuss recent electrophysiological findings that offer an alternate view of hippocampal and medial entorhinal function. These findings suggest complementary contributions of the hippocampus and medial entorhinal cortex in support of episodic memory, wherein hippocampal networks encode sequences of events that compose temporally and spatially extended episodes, whereas medial entorhinal networks disambiguate overlapping episodes by binding sequential events into distinct memories.
Does hippocampal activity embody the cognitive map? One should expect the neural instantiation
of Tolman's [1] cognitive map to contain units (neurons) that are fully
allocentric, that is, identify places in the environment independent of the
subject's perspective (egocentric direction) and ongoing behavior. Furthermore,
one should expect that the neural ensemble composed of these units would be
holistic; that is, all the neuronal representations should be tied to one
another and change together between environments. And, if the map is to suit
the purpose Tolman proposed in guiding behavior according to expectancies, the
map should signal the locations of current goals.Initially, hippocampal place cells seemed to satisfy key criteria for elements of Tolman's
cognitive map. The first complete study characterized place cells as signaling
an animal's location in the environment independent of egocentric direction and
ongoing behavior, as would be expected of the units in an allocentric representation
[2]. An expansive literature followed on the initial observations,
and many interpreted the results as support for the claim that the neural
substrate for the cognitive map lies in the circuitry of the hippocampus
[3-9].However, even in
the early data there were loose ends. Location related hippocampal neuronal
activity tells us only where the animal is, not where it plans to go, as is
Tolman's intended function of a cognitive map [10]. Succeeding studies
directly refuted the idea that the hippocampal network contains purely
allocentric representations and a holistic map. Inconsistent with a holistic
representation, simultaneously recorded place cells respond differently and
independently to changes in environmental cues or task demands (e.g., [11-14]). Furthermore, inconsistent with allocentric representation,
the activity of most hippocampal neurons is dependent on egocentric spatial
parameters, including the direction and speed of the animal's movements
[15]. Indeed, place cells reliably provide an allocentric
signal only under highly constrained conditions where all perceptual cues,
behaviors, and cognitive demands are held constant. In addition, hippocampal
neuronal activity has been associated with a variety of nonspatial cues,
behaviors, and task demands [16-27], consistent with additional findings showing a critical role for
the hippocampus in nonspatial as well as spatial learning and memory [28-30]. Also, several recent studies have
provided compelling evidence that so-called place cells are strongly influenced
by nonspatial cognitive demands in animals performing spatial memory tasks
[31-37], and thus signal where
the animal is only in particular circumstances associated with a behaviorally
salient task.In sum, place
cells do identify where the animal is when important things happen. But place
cells do not carry a reliable allocentric signal, and populations of place
cells do not operate as a holistic representation of space or anticipate the
locations of goals. Therefore, hippocampal neurons do not have the requisite
properties to support Tolman's cognitive map. By contrast, the findings
indicate that hippocampal neurons represent events in the places where they
occur, consistent with current views of hippocampal involvement in episodic
memory (e.g., [38, 39]).The recent
discovery of spatial firing patterns in the cortex immediately adjacent to the
hippocampus has refocused the search for the cognitive map to a zone within the
medial entorhinal area [36, 40–43]. A majority of the data describes the spatial
firing patterns of principal neurons in the medial entorhinal cortex, and more
specifically how a proportion of these neurons, the so-called “grid cells,”
exhibit an intriguing and unique spatial firing pattern with several interesting
properties. First, the relative angles and densities of peaks within grids of
neighboring cells remain invariant both across environments and in response to
changes in local cues [41]. Second, while grid fields of
medial entorhinal neurons remain stable in response to modest environmental
manipulation, hippocampal CA3 neurons change their rate of firing (“rate
remapping,” [44]). In response to more significant environmental
change, grid fields of local ensembles of medial entorhinal neurons rotate
while maintaining relative geometric consistency, whereas CA3 neurons fire in a
different location (“global remapping”), [44]. Thus, in response
to environmental manipulation, changes in medial entorhinal activity are more
systematic and predictable than corresponding hippocampal CA3 responses, and
consequently more stable as sensory inputs change. Third, while lacking any
obvious topographic organization of space, the relative size of medial
entorhinal grid fields changes systematically along a dorsal-ventral axis
[41]. Although medial entorhinal cells are influenced by
egocentric parameters of head direction and velocity, [42],
these findings modestly suggest that some version of the cognitive map may
reside within the medial entorhinal cortex, rather than the immediately
adjacent hippocampus. This interpretation will be argued in several other
papers of the current volume. However, here we will suggest an alternate view
driven by recent data that includes our own experiment wherein sensory cues
were held constant throughout the experiment [36]—that spatial representations observed in
medial entorhinal cortex may make a specific contribution to episodic memory.
2. EPISODIC MEMORY
2.1. Memory for order
The hippocampus is
strongly implicated in spatial memory and navigation as evidenced by both
behavioral and physiological studies. At the same time, a convergent stream of
behavioral, physiological, and computational modeling data indicate that
hippocampal processing is critical for episodic memory [45-57].
How can these two seemingly distinct lines of evidence be reconciled?Current
conceptions of episodic memory emphasize the temporal organization of sequences
of events as they unfold over time and space [58]. Representations of
events are composed as associations between specific objects, actions, and the
locations where they occur. Complete episodes are composed of unique sequences
of events [38]. Recent experiments have revealed a critical role
of the hippocampus in memory for sequences of events that compose unique
episodes [47, 59]. In addition, episodic memory
also relies on the capacity to distinguish event sequences that share common
elements [60]. This property of episodic memory is
especially evident in spatial memories, for example, we are usually very good
at remembering unique events that occur day by day as we take the same route to
work each day. Computational models suggest that the ability to disambiguate
overlapping elements from multiple experiences may be a critical feature of
hippocampal function that contributes to episodic memory [53].
Consistent with this view, rats with hippocampal lesions fail on a sequence
disambiguation task that involved two series of events that contain overlapping
items [45].Additional support
for sequencing and disambiguation of serial events by hippocampal networks
comes from analyses of hippocampal neuronal activity in animals performing
spatial memory tasks. In one study, rats were trained on the classic spatial
T-maze alternation task in which successful performance depends on
distinguishing left- and right-turn episodes to guide each subsequent choice
[37]. If hippocampal neurons encode each sequential behavioral
event within one type of episode, then neuronal activity at locations that
overlap in left- and right-turn trials should vary according to trial type.
Indeed, virtually all cells that were active as the rat traversed these common
locations were differentially active on left- versus right-turn trials. Despite
modest differences in the proportion of neurons that exhibit this pattern of
activity across studies—likely due to
differences in training protocols—similar results
have been observed in several versions of this task [31–35, 37, 61]. These findings suggest a reconciliation of the
spatial and episodic memory views of hippocampal function: place cells
represent the series of places where events occur in sequences that compose
distinct episodic memories.
2.2. Temporal context
In order to
correctly trigger a series of event representations within a particular
episode, the hippocampus requires a mechanism to bind its representations of
event sequences according to the appropriate episode they compose. One
suggestion is that sequences are bound by a shared temporal context [49, 62] and that the mechanism for
contextual binding involves context sensitive neurons that fire for prolonged
periods to bridge sequences of events that occur within a particular context
[63]. Here, we review evidence suggesting that the context
sensitive neurons exist in the medial entorhinal cortex and serve a function
complementary to that of hippocampal place cells which encode discrete events.Thus far, all
observations of grid field activity patterns in medial entorhinal cortex are
derived from animals foraging in random directions within an open field. In
fact, Derdikman et al. [64] report that the grid structure breaks down when animals
are constrained to make hairpin turns within the previously unconstrained open
field. This is notable because in the standard, random foraging experimental
protocol, spatial cues provide the only regularities and constraints. In
contrast, what differed between the hairpin turn maze and the open field
condition was the imposition of behavioral constraints; spatial cues were held
constant. Importantly, it is only under the unconstrained open field condition
that hippocampal cells display purely allocentric spatial firing patterns.
Perhaps where stimulus or behavioral regularities are imposed, the activity of
neurons in medial entorhinal cortex, like neurons in the hippocampus, might
reflect the corresponding regularities embedded in the task protocol.In a recent study,
we adopted the same spatial memory task used previously [37] to
compare the activity of hippocampal and medial entorhinal neurons in animals
performing a continuous spatial alternation on a T-maze in which hippocampal
neurons encode sequences of locations traversed and disambiguate overlapping
routes [36]. Two important considerations are worth mentioning
here. First, we were explicitly interested in comparing how medial entorhinal
and hippocampal neurons uniquely represent aspects of the continuous spatial
alternation, rather than in an analysis of grid cell properties. Our
interpretation of our data therefore addresses the contribution of medial
entorhinal cortex to episodic memory, not whether a grid field forms on a
T-maze. Second, just as the expansive place cell literature relies almost
exclusively on observations of hippocampal activity in situations that neither
require any manner of hippocampal processing nor impose any memory demands, our
experimental design exploited the capacity of medial entorhinal neurons to
encode spatial information. Whether the task is hippocampal or entorhinal
dependent is not relevant to our interpretations. Insofar as the continuous
spatial alternation is not a hippocampal dependent-task, it is worth noting
that hippocampal dependence is neither an operational definition of, nor a
pre-requisite for, memory.We trained rats to
perform the spatial alternation task on a T-maze that included return arms that
connected the end of each goal arm to the starting end of the central stem
(Figure 1). A left-turn trial began as the animal departed the right goal area,
ran down the return arm to the central stem, traversed the central stem, and
made a left-turn into the left goal area to retrieve a water reward. Similarly,
a right-turn trial began when the animal departed the left goal area, returned
to and traversed the central stem, and made a right turn into the right goal
area. Drawing on the model of episodic memory noted above, each left- or
right-turn trial can be considered a unique episode, constructed by connecting
sequential behavioral events identified by a series of loci along the maze.
Areas that lie along the central stem constitute overlapping elements of both
types of episodes, and are indeed represented differently by hippocampal
neurons depending on the ongoing episode (Figure 2, [36, 37]). Furthermore, consistent with previous reports [40, 65], activity of neurons in medial entorhinal cortex also
signals an animal's position along the maze. Though we did not witness the
development of a grid-like firing pattern on the T-maze, a proportion of our
medial entorhinal neurons did exhibit a high degree of spatial specificity
[36]. For example, the medial entorhinal cell shown in Figure 3
fired predominantly at the proximal end of the central stem during both left-
and right-turn trials, while remaining largely silent through other regions of
the maze.
Figure 1
T-maze continuous alternation. Blue line indicates left-turn trial; red line indicates
right-turn trial. Small green circles represent reward sites.
Figure 2
The activity of two example hippocampal neurons represented as false-color rate maps
to illustrate differential firing on left- versus right-turn trials. (a). This unit was significantly more
active on left-turn trials: significant main effect of segment (F
6,420 = 91.05; P < .00001) and
interaction (F
6,420 = 2.58; P < .02); log-likelihood ratio = 0.2; p
correct = 0.6; p
chance = 0.08. (b). This
unit was significantly more active on right-turn trials: significant main effect of segment F
6,252 = 68.3; P < .00001) and interaction F
6,252 = 2.92; P = 0.009); log-likelihood ratio = 1.22; p
correct = 0.63; p
chance = 0.07. Color bars indicate firing rate in Hz.
Figure 3
Location related firing of a medial entorhinal neuron that did not fire differentially on
left- versus right-turn trials. Significant main effect of segment (F
6,238 = 44.43; P < .00001); loglikelihood
ratio = 2.5; p
correct = 0.72; p
chance = 0.006. Color bars indicate firing rate in Hz.
Many of our medial
entorhinal neurons that exhibited spatial specificity also exhibited
differential firing along the central stem of the maze during left- and
right-turn trials, similar to hippocampal neurons [36]. The
patterns of neuronal activity illustrated in Figure 4 represent typical
trial-type specific activity exhibited by medial entorhinal neurons. Some
medial entorhinal cells fired selectively during the trial and distinguished
left-turn and right-turn trials. For example, the cell shown in Figure 4(a) was
selectively active when the rat was near the end of the central stem and fired
at a higher rate during right-turn compared to left-turn trials. However, most
medial entorhinal neurons showed only crude spatial specificity. For example,
the cell shown in Figure 4(b) fired somewhat indiscriminately through different
regions of the maze, and although active along the entire central stem, was
significantly more active on left-turn trials. This pattern of activity was an
exclusive feature of medial entorhinal neurons, such that we observed no
hippocampal units with poorly localized, trial-type specific firing that
extended the length of the central stem [36].
Figure 4
Firing patterns of two representative medial entorhinal neurons that reflect both trial
disambiguation and a low degree of spatial specificity. (a). This unit was significantly more active
on right-turn trials: significant main effect of segment (F
6,392 = 11.73; P < .00001), trial type
(F
1,392 = 7.32; P < .00071) and interaction (F
6,392 = 2.22; P < .04); log-likelihood ratio = 4.62;
p
correct = 0.67; p
chance = 0.006. (b). This unit was significantly more active on left-turn trials:
significant main effect of segment (F
6,280 = 3.83; P < .0011), trial type (F
1,280 = 4.87; P < .03)
and interaction (F
6,280 = 1.83; P < .09); log-likelihood ratio = 1.29; p
correct = 0.71; p
chance = 0.004.
Color bars indicate firing rate in Hz.
We used a two-way
ANOVA and log-likelihood estimation to quantitatively compare the incidence and
robustness of trial-type disambiguation in medial entorhinal and hippocampal
neurons. Dividing the central stem into seven equal segments, we used a two-way
ANOVA to compare the spatial firing patterns on segments of the central stem
between left-turn and right-turn trial types for each cell [37].
We considered that a significant main effect of trial type or a trial type by
segment interaction qualified a cell as differentiating left- from right-turn
trials. A significant main effect of segment without a significant main effect
of trial type or trial type by segment interaction denoted location-specific
activity only. The log-likelihood ratio [66], on the other
hand, represented the degree to which firing patterns on left-turn and
right-turn trials differed, and thus allowed us to measure the difference in
the firing patterns across trial types, rather than knowing simply that they
differed. The log-likelihood ratio was calculated as follows: 1n
p[r | L, x]/p[r | R, x], where p[r | L, x] is the probability density
function of left-turn (L) trials at position x, evaluated at the observed
firing rate r, and p[r | R, x] is the equivalent function for right-turn (R) trials [66]. For each cell, log-likelihood ratios were summed over all central
stem bins for each trial. Where the log-likelihood sum is greater than zero,
maximum likelihood analysis predicts that the data came from a left-turn trial;
otherwise, a right-turn trial is predicted. We calculated the average absolute
value of the summed log-likelihood ratio, such that larger values of this term
indicate firing-rate patterns that are statistically more distinct (for a more
detailed description, see [36]).Using the two-way
ANOVA, we identified neurons in the hippocampus and medial entorhinal area that
distinguished trial type as animals traversed the central stem. Based on the
two-way ANOVA, 56% of medial entorhinal neurons (23/41 with place fields on the
central stem) were significantly more active on either right- or left-turn
trials, whereas 33% (16/48) of hippocampal neurons exhibited differential
firing on the central stem. Moreover, the log-likelihood estimation revealed
that medial entorhinal neurons more robustly distinguished left- from
right-turn trials than did hippocampal neurons, such that the average
log-likelihood ratio for medial entorhinal neurons was significantly greater
than for hippocampal neurons (MEC, 2.82; Hippocampus, 1.7; Wilcoxon rank-sum test, P < .003). In other words, firing patterns of medial entorhinal neurons
were on average more distinct on either left- or right-turn trials than were
hippocampal neurons.Two additional
measures were applied to describe how the patterns of activity in hippocampal
and medial entorhinal neurons differed along the central stem during left- and
right-turn trials [36]. The first measure, p
correct, is based on a maximum-likelihood guess
performed for each trial compared against the actual outcome of that trial, and
thus describes how accurate the log-likelihood estimate is for each trial type.
To calculate p
correct, we
performed a maximum likelihood analysis using the conditional density functions
as described above. p
correct represents the number of times that prediction was correct, divided by the
total number of trials. Therefore, p
correct is the average trial-by-trial probability that the log-likelihood analysis
gives the correct answer for each trial type: a population that more
consistently and significantly differentiates left- from right-turn trials will
have a higher p
correct.
The second measure, p
chance,
is the average probability that firing patterns across left- and right-turn
trials arose by chance, given a p
correct of 0.5 (i.e., the firing rate contains no trial-specific information, which is
necessary to avoid biasing the calculation). To calculate p
chance, we evaluated the following formula: Pnk = n!/k!/(n − k)!(0.5)0.5(1−, where n is the number of trials, and k is the number of apparently correct answers from maximal likelihood
analysis. To get p
chance,
we summed Pnk for all values of k greater
than or equal to the number associated with our measured value of p
correct. A p
chance = 0.05 determined
that a cell could successfully distinguish trial type.Again,
medial entorhinal neurons had a significantly higher mean p
correct than hippocampal neurons (MEC, 70%;
Hippocampus, 63%; Wilcoxon rank-sum test, P < .0001), indicating that
the activity of medial entorhinal neurons along the central stem more
successfully predicted trial type than hippocampal neurons. Correspondingly,
the difference in firing among left- and right-turn trials of medial entorhinal
neurons was on average less likely to have occurred by chance than that of hippocampal
neurons (p
chance equal to
or less than 0.05: 90% MEC; 50% Hippocampus).While the ANOVA and log-likelihood estimation did not always agree on specific units,
together they converged on the same conclusion; just as hippocampal units did
not exclusively encode information about space, medial entorhinal neurons
likewise exhibited location-related firing modulated by mnemonic demands.
Furthermore, medial entorhinal neurons performed better than hippocampal
neurons at distinguishing trial type on our version of the continuous spatial
alternation [36].Conversely, hippocampal neurons
showed greater spatial specificity than medial entorhinal neurons, as is
evident by directly comparing the spatial firing patterns displayed in Figures
3 and 4. Our visual observations were bolstered by three quantitative measures—performed on all
hippocampal and medial entorhinal units with a firing field somewhere on the
maze—meant to assess
spatial selectivity: place field size, spatial tuning, and spatial information
rate. On all three measures hippocampal and medial entorhinal activity differed
significantly. For example, average hippocampal place field size for all units
with location related activity on the maze was significantly smaller than that
of medial entorhinal neurons (256.8 cm2 versus 330.8 cm2,
resp.; Wilcoxon rank-sum test, P < .0003). The degree of spatial
tuning, or the ratio of firing inside versus outside a place field, for
hippocampal neurons was on average significantly higher than for medial
entorhinal neurons (11.5 versus 3.0, resp.; Wilcoxon rank-sum test, P < 8.8E–16). The amount of spatial information
conveyed by hippocampal neurons also was significantly greater than that of
medial entorhinal neurons (2.02 bits/second versus 0.89 bits/second, resp.;
Wilcoxon rank-sum test, P < .00001).Together the results of this study
suggest that disambiguation of overlapping experiences occurs prior to the
hippocampus, and that hippocampal and medial entorhinal circuits play distinct and
complementary roles in the continuous spatial alternation. Medial entorhinal
neurons more successfully distinguished task related episodes in the context of
left- versus right-turn trial type, whereas hippocampal neurons provided a
greater degree of spatial specificity. Together both regions supply requisite
elements of a neural code for particular events as they occur within unique
episodes.Since the neural circuitry among
these brain regions constitutes a series of loops [67], it is difficult
to positively attribute specific functions to individual brain regions.
However, very recent evidence from observations of CA1 neuronal activity in
animals with lesions to layer III of medial entorhinal cortex offers crucial
support [68]. The results demonstrate that precise spatial coding
of CA1 neurons is more dependent on this direct entorhinal input than on
projections from CA3 which provide indirect input from layer II of medial
entorhinal cortex [68], indicating that the manner of spatial
information processing most commonly observed in CA1 is the result of a clear
progression from medial entorhinal cortex to hippocampus.
3. HOW DOES THE MEDIAL ENTORHINAL CORTEX CONTRIBUTE TO EPISODIC MEMORY?
Our recent experimental results
confirm that medial entorhinal neurons carry a spatial signal. However, as
noted above, most of these neurons do not fire at discrete locations associated
with particular trial events, as do hippocampal neurons. Instead, many medial
entorhinal cells show strong context sensitivity, outperforming hippocampal
neurons in distinguishing left-turn and right-turn trials. Furthermore, the
prolonged firing periods of medial entorhinal cells are consistent with the
characterization of context sensitive neurons that could bind a series of
hippocampal representations of punctate events [63].A growing body of evidence
supports the notion that the medial entorhinal area is part of the
parahippocampal region that processes contextual representations. This evidence
is derived from knowledge about the anatomical pathways of the hippocampal
system and from recent functional imaging studies [39].
Inputs to the hippocampus arrive via the surrounding cortical areas that
compose the parahippocampal region [67]. This region can be
subdivided into the perirhinal cortex, the parahippocampal cortex (called
postrhinal cortex in rodents), and the entorhinal cortex. Most neocortical
inputs to the perirhinal cortex are derived from association areas that process
unimodal sensory information about qualities of objects (i.e., “what”
information), whereas most of the neocortical inputs to the parahippocampal
cortex (called postrhinal cortex in rats) originate in areas that process polymodal
spatial (where) information.Subsequently, the “what”
and “where” streams of processing remain largely segregated as the perirhinal
cortex projects primarily to the lateral entorhinal area, whereas the
parahippocampal cortex projects mainly to the medial entorhinal area. While
there are also some connections between the perirhinal and parahippocampal
cortices and between the entorhinal areas, the “what” and “where” information
mainly converge within the hippocampus. Hippocampal efferents back to the cortex
involve feedback connections from the hippocampus successively back to the
parahippocampal region and thence to neocortical areas from which the inputs
originated. This anatomical evidence suggests that, during encoding, “what”
information carried in the perirhinal-lateral entorhinal stream is combined
with “where” information carried in the parahippocampal-medial entorhinal
stream and the hippocampus associates items and their spatial context. When an
item is subsequently presented as a memory cue, the hippocampus completes the
full pattern and mediates a recovery of the contextual representation in the
parahippocampal cortex and medial entorhinal area, and the recovery of context
constitutes the experience of episodic recollection.In support of this model, evidence from functional imaging studies in humans indicates that the
parahippocampal cortex component of the “where” stream represents spatial
context. One line of evidence comes from the work of Kanwisher and colleagues,
showing that the parahippocampal region is activated when people view spatial
scenes and not objects or faces [69]. The other line
of evidence comes from work of Bar and colleagues, showing that the
parahippocampal cortex is activated when people view objects that have strong
spatial contextual associations (e.g., a refrigerator, a roulette wheel, [70]). Similarly, a cellular (fos) imaging study indicates that
the postrhinal cortex also is activated in rats by novel spatial arrangements
of cues [71]. In addition, Aminoff et al. [72] reported that
adjacent components of the parahippocampal cortex are activated by spatial
context, and that this activity emerges as people view abstract patterns that
were elements of newly learned spatial patterns or simply temporally
associated. These findings extend the potential role of the parahippocampal
cortex to temporal contextual representations as well as spatial context. Such
a view is consistent with the frequent observation that the parahippocampal
region is activated when humans recollect items in the context in which they
were learned (reviewed in [39]).We lack studies that compare response properties of the parahippocampal cortex and the medial
entorhinal area. However, the combined data from functional imaging of the
parahippocampal cortex in humans and animals and our recent study of spatial
firing properties of medial entorhinal neurons suggest that both the
parahippocampal cortex and medial entorhinal area components of the “where”
pathway may be specialized for the processing of spatial and temporal context
in humans and animals. Much work remains to be done to test this hypothesis.
However, we believe there is sufficient evidence to consider the medial
entorhinal area as part of a contextual representation system rather than the
embodiment of a cognitive map that guides spatial navigation.
Authors: Vegard Heimly Brun; Stefan Leutgeb; Hui-Qiu Wu; Robert Schwarcz; Menno P Witter; Edvard I Moser; May-Britt Moser Journal: Neuron Date: 2008-01-24 Impact factor: 17.173
Authors: Andrew M Ward; Elizabeth C Mormino; Willem Huijbers; Aaron P Schultz; Trey Hedden; Reisa A Sperling Journal: Neurobiol Aging Date: 2014-07-03 Impact factor: 4.673